This document proposes a novel service providing protocol with QoS support over mobile ad-hoc networks (MANETs). It collects a list of available service providers and scores them based on reliability and response time to select the best provider. It uses a hidden Markov model to estimate the current state of the network as stable or dynamic, and service availability as normal or faulty. Based on the estimated state, different selection strategies are used to minimize hand-offs and provide reliable service, such as selecting providers with minimum response time in a stable, normal state or adding factors like hop count or mean time to failure in dynamic or faulty states. The method was evaluated in a MANET emulator and shown to improve disconnection and SLA change rates

1. V. Babaiyan, O. Bushehrian
Dept. of Computer Eng. and IT, Shiraz University of Technology Shiraz, Iran
[v.babaiyan, bushehrian]@sutech.ac.ir
A Novel Service
Providing Protocol
With QoS Support Over
MANET’s
1

2. Out line
Introduction
Problem statement
The proposed service selection method
State estimation using HMM
Evaluation and experimental results
Conclusion
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3. I nt roduct ion
Mobile ad-hoc networks (MANET’s) consist of mobile
nodes interconnected by multi-hop wireless paths.
Application Level: A set of Service providers and
Service Consumers deployed over MANET
Example: A planner Service, A Logger Service
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4. Problem St at ement
Service Assignment Problem:
Once a node demands a service: How to select from
available services?
Criteria: Reliability and response time
Objective: Select the fastest service provider
which provides a reliable service( in terms of DC
rate)
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5. The proposed
Solut ion
Assumptions:
Service providers with different QoS(RT)
An on-demand based service discovery method
The proposed solution:
Collect the list of service providers.
Score the providers according to their reliability and
response time.
Select the best service provider.
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6. Paper I dea
Causes of unreliable service providing:
Network dynamicity:
Neighbor nodes frequently move away each other
Service Dynamicity:
A service provided by a node fails or goes out of service
frequently
Service providers are scored regarding the
above factors
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7. 7
Paper I dea
1
2
3
4
This node needs service x
X is provided by both node 2 and 4
Scoring based on the first factor:
Dynamic network: node 2 is more reliable than node 4
Stable network: same score
Scoring based on the second factor:
Stable Service providing: same score
Dynamic service providing: The node with the less
previous DC rate gains better score

8. The Service select ion
met hod
8
Requester Node:
Requests for service
x
Service Manager:
Collects the list of
providers of x
Service Manager:
Estimates the current
state of the system
Service Manager:
Scores the provides
according to the current
system state and
proposes the best one

9. 9
EnvironmentEnvironment
Requester
Program
Node
Service
Manager
Provider
Program
Node
Service
Manager
Node
Service
Manager
…. ….
The Proposed
Prot ocolThe protocol is executed by a management agent installed on each node called
Service Manager (SM).
Each SM in the network is responsible to transmit the internal and external
messages
ServiceReq
ServiceRep

10. 11
The Proposed
Prot ocol
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“ServiceRequest”

11. 12
6
2
2
4
4 3
a
b
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“ServiceRequest”
The Proposed
Prot ocol(ServiceReq)

12. ServiceReply
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13. The requester scores the service providers
based on the current state of the network
Hidden Markov Model(HMM) is used to
estimate the current state of the network.
Define the System States
Define the local observations
To estimate the current state each node uses the
forward-backward algorithm
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St at e Est imat ion
using HMM

14. St at e Est imat ion
using HMM
The System State is defined as the composition of
networkState, and ServiceAvailiblity.
networkState values: {‘Stable’, ‘Dynamic’}
ServiceAvailiblity values: {‘Normal’, ‘Faulty’}.
State1: (Stable, Normal)
State2: (Stable, Faulty)
State3: (Dynamic, Normal)
State4: (Dynamic, Faulty)
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“service selection is performed depending on the current
state of the environment.”

15. Est imat ing t he
net work st at eThe following factors are observed by each node:
Disconnection Rate
Route Change Rate in the local Routing Table
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16. The Select ion
St rat egy
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State: (Stable, Normal) : Min (Response Time)
State: (Stable, Faulty) : Min(Response Time + 1/MTTF)
State: (Dynamic , Normal) : Min (Response Time + Hop Count)
State: (Dynamic, Faulty) : Min(Response Time + Hop Count + 1/MTTF)

17. Evaluat ion
The proposed method was evaluated using a MANET
Emulator implemented in Java Language.
The emulator was configured to transit between system
states with defined probabilities:
Case1: Unstable system: Dynamic Network, Faulty Service providers
Case2: Stable System: Stable Network, Normal Service providers
Case3 : Changeable System
In each case the DC rate and SLA change was recorded.
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18. Evaluat ion
The observation Matrix:
19
System States
Observations
)Route Change Rate, Disconnection Rate(
(L, L) (L, H) (H, L) )H, H(
(Stable, Normal) 99 0 1 0
(Stable, Faulty) 1 99 0 0
(Dynamic, Normal) 0 0 1 99
(Dynamic, Faulty) 0 1 0 99

19. 20
Evaluat ion Result s:
Unst able Syst em

20. 21
Evaluat ion Result s:
St able Syst em

21. Conclusion
We have proposed a novel service providing protocol which
applies the HMM to estimate the network state based on the
local observations.
We also have proposed the actions to be taken at each network
state by the clients.
Our protocol selects service providers at each network state
such that the minimal amount of hand-off is resulted, so a
reliable service is provided to the clients.
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